SCALING RECOMMENDATION MODELS FOR A GLOBAL AUDIENCE: CHALLENGES, STRATEGIES, AND ARCHITECTURES
Keywords:
Global Recommendation Models, Personalized User Experiences, Data Diversity, Regional Adjustments, Hybrid ApproachAbstract
Today's digital world relies heavily on recommendation models to personalize experiences and drive user engagement across various domains. However, scaling these models to cater to a global audience presents significant challenges due to the diversity in user preferences, cultural nuances, and infrastructural constraints. This article explores the challenges and considerations that arise when scaling recommendation models for a global audience and discusses potential solutions through various architectures and strategies. We present a case study of an online video streaming platform serving over 100 countries to demonstrate the successful implementation of these approaches in a real-world scenario.
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Copyright (c) 2024 Vatesh Pasrija, Supriya Pasrija (Author)
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